The Challenge
by Samira Shirzaei and Jeffery Smith (Auburn University)
As presented at the 2018 Winter Simulation Conference
We focus on a service system in which the customer arrivals are non-stationary and our goal is to determine a server staffing schedule that ensures that arriving customers do not experience long and/or unpredictable queue times.
Introduction
Our goal is to optimize a service system operation like a check-in counter in an airport, by focusing on the staffing levels to best control the customers’ waiting times.
The Solution
Initial model
Our basic model’s characteristics are similar to the one used in Smith and Nelson (2015).
Input Analysis for Arrival Data Set
We start with the passenger arrival data for 5 days from an airport check-in counter.
Problem Description
From a customer service perspective, the best system is one that has lots of servers so that no arriving customer waits.
Empirical Approach
To clarify the importance of having appropriate staffing levels in non-stationary processes, we show some examples.
- Analyze arrival data using HistoRIA
- Use arrival rates in simulation
- Define staffing levels per time bucket
- Evaluate waiting-time constraints
- Iterate to minimize cost
The Business Impact
Conclusions
In real customer service systems, arrival processes are often non-stationary. This makes resource planning difficult due to competing objectives of customer satisfaction and cost control.
Author Biographies
Samira Shirzaei is a doctoral student at Auburn University with research interests in simulation and operations research.
Jeffrey S. Smith is the Joe W. Forehand Professor of Industrial and Systems Engineering at Auburn University.
References
Ansari, M. et al. (2014). HistoRIA: A New Tool for Simulation Input Analysis.
Feldman, Z. et al. (2008). Staffing of Time-Varying Queues.
Green, L. V. et al. (2007). Coping with Time-Varying Demand.
Whitt, W. (2007). Queueing Models to Set Staffing Requirements.